Inference on common parameters in panel data models with individual-specific fixed effects is a classic example of … small), but this solution is not applicable to all panel data models of interest. Another solution, which applies to a … larger class of models, is "large-T" bias correction [pioneered by Hahn and Kuersteiner (Econometrica 70(4):1639-1657, 2002 …

Bias correction can often improve the finite sample performance of estimators. We show that the choice of bias … estimate of the bias is asymptotically linear. It is also shown that bootstrap, jackknife, and analytical bias estimates are … estimators the straightforward bootstrap bias correction gives the same higher-order variance as more complicated analytical or …

local and marginal treatment effects. First, we characterize the bias, due to the omitted variables U, of (nonparametric …) regression and instrumental variables estimands, thereby generalizing the classic linear regression omitted variable bias formula …

Kotlarski's identity has been widely used in applied economic research based on repeated-measurement or panel models …

major limitations, such as the absence of poverty data, sampling bias due to incomplete telephone coverage in many … weights were adjusted to correct the sampling and nonresponse bias. This paper examines whether reweighting procedures and the … Survey of Wellbeing via Instant and Frequent Tracking methodology can eliminate the bias in poverty estimation based on the …

Missing data or missing values are a common phenomenon in applied panel data research and of great interest for panel … data unit root testing. The standard approach in the literature is to balance the panel by removing units and/or trimming a … common time period for all units. However, this approach can be costly in terms of lost information. Instead, existing panel …

inconsistent. The bias arises in settings with many regressors because the normalized OLS design matrix remains asymptotically … random and correlates with the regression error when only weak (but not strict) exogeneity holds. This bias' magnitude … increases with the number of regressors and their average autocorrelation. We propose an innovative approach to bias correction …